1. Field of the Invention
The present invention relates to a coefficient updating method for an adaptive filter, and more specifically to a coefficient updating method which is capable of monitoring the convergence condition of an adaptive filter when updating coefficients and capable of stopping the updating immediately if convergence occurs.
2. Description of the Related Art
In recent years, there have been demands for a reduction in the noise which is generated by devices such as information processing equipment, for the purpose of improving the work environment in offices and other areas. In this regard, active noise control apparatuses have gained attention as noise reduction devices. The principle of the active noise control apparatus is that of using an adaptive filter to generate a pseudo-noise having the same amplitude but the opposite phase of the noise and to superimpose this on the noise to cancel out the noise. This technique is particularly effective as a method for suppressing low-frequency noise, which is difficult to suppress with passive noise reduction techniques.
A technology central to active noise control is that of an adaptive algorithm which is used to calculate the filter coefficients for an adaptive filter which synthesizes the pseudo-noise of the same amplitude but opposite phase of the noise, the most typical known adaptive algorithm being the filtered-X/LMS (least mean squares) method. In the LMS method, the filter coefficients of an adaptive filter are calculated as corrections are made so that the difference (Error) between the input of an error convergence microphone located at the position at which the reduction of noise is desired and the pseudo-noise is minimized.
However, with active noise control there is the problem of only being able to indirectly observe the error via the error convergence microphone, and if the transmission system between this error convergence microphone and the adaptive algorithm (known here as an error scattering transmission system, because the error is dispersed along the time-axis direction) cannot be made to approximate unity, it is necessary to place a filter (known as a estimation scattering or C filter) the before processor using the LMS method. This adaptive algorithm is known as the filtered-X/LMS method.
The transmission time of the white noise which is output from a white noise generator and used for filter coefficient learning (that is, the time required for update of coefficients) is calculated using the equation EQU T (R)=0.23 RK (2-K) I,
where:
R is the target prediction accuracy, PA0 K is the step gain, and PA0 I is the number of taps (256 to 4096).
Because the transmission time of the above-noted white noise is calculated as a fixed value by the above equation, a problem exists in that there is not necessarily coincidence between the above white noise transmission time and the actual amount of time required to reach the condition of convergence. In such a case, it could happen that the transmission of white noise continues even after convergence is reached, or on the other hand, that the transmission of white noise is stopped, even though convergence has not yet been reached. In the case of an active noise control apparatus in particular, changes in the environment (such as a change in the temperature) cause a change in the transmission characteristics, leading to cases in which the step gain of the adaptive filter must be changed, and when this happens it is necessary to make the white noise transmission time long enough to include the time for these changes. As a result, there was the problem that filter coefficient updating required an extremely long period of time.